from dataclasses import dataclass
from config.config import ConfigManager


@dataclass
class RiskParams:
	"""风险管理参数配置"""
	max_portfolio_risk: float = 0.02  # 组合最大风险敞口比例
	per_trade_risk: float = 0.01  # 单笔交易风险比例
	max_sell_ratio: float = 0.3  # 风险控制允许的最大卖出量
	max_position_ratio: float = 0.2  # 单个标的持仓上限比例
	min_position_ratio: float = 0.1  # 单个标的持仓下限比例
	max_portfolio_exposure: float = 1.0  # 持仓组合总风险敞口上限
	stop_loss_pct: float = 0.05  # 止损幅度百分比
	take_profit_pct: float = 0.15  # 止盈幅度百分比
	volatility_window: int = 20  # 波动率计算窗口
	min_trade_unit: int = 100  # 最小交易单位
	max_leverage: float = 2.0  # 最大杠杆倍数


class RiskManager:
	"""统一风险管理模块"""

	def __init__(self, config: ConfigManager):
		"""
		:param portfolio_manager: 持仓管理器实例
		:param risk_params: 风险参数配置
		:param volatility_calculator: 波动率计算函数接口
		"""
		self._config = config
		self.params = RiskParams(
			per_trade_risk=self._config.get('risk.per_trade_risk'),
			max_position_ratio=self._config.get('risk.max_position_ratio'),
			min_position_ratio=self._config.get('risk.min_position_ratio'),
			max_portfolio_exposure=self._config.get('risk.max_portfolio_exposure'),
			max_sell_ratio=self._config.get('risk.max_sell_ratio')
		)

	# self.volatility_calc = volatility_calculator or self.default_volatility

	def bind(self, engine):
		self.engine = engine

# def default_volatility(self, symbol: str, window: int) -> float:
#     """默认波动率计算（ATR法）"""
#     if symbol not in self.pm.hist_data:
#         return 0.0

#     data = self.pm.hist_data[symbol]
#     if len(data) < window:
#         return 0.0

#     high_low = data['high'] - data['low']
#     high_close = (data['high'] - data['close'].shift()).abs()
#     low_close = (data['low'] - data['close'].shift()).abs()
#     tr = pd.concat([high_low, high_close, low_close], axis=1).max(axis=1)
#     return tr.rolling(window).mean().iloc[-1]

# def calculate_position_size(
#     self,
#     symbol: str,
#     price: float,
#     direction: OrderDirection
# ) -> int:
#     """综合风险计算头寸规模"""
#     # 基础头寸计算
#     base_size = self._base_position_size(price)

#     # 波动率调整
#     volatility_adj = self._volatility_adjustment(symbol, price)

#     # 集中度限制
#     concentration_adj = self._concentration_limit(symbol, price)

#     # 杠杆限制
#     leverage_adj = self._leverage_constraint(base_size * price)

#     # 综合计算最终头寸
#     final_size = min(
#         base_size,
#         volatility_adj,
#         concentration_adj,
#         leverage_adj
#     )

#     # 确保最小交易单位
#     return max(
#         self._round_lot(final_size),
#         self.params.min_trade_unit
#     )

# def _base_position_size(self, price: float) -> int:
#     """基础头寸（基于可用资金和风险比例）"""
#     risk_capital = self.pm.total_equity * self.params.per_trade_risk
#     return int(risk_capital // price)

# def _volatility_adjustment(self, symbol: str, price: float) -> int:
#     """波动率调整系数"""
#     atr = self.volatility_calc(symbol, self.params.volatility_window)
#     if atr == 0:
#         return float('inf')

#     max_risk_units = (self.params.per_trade_risk * self.pm.total_equity) / atr
#     return int(max_risk_units // price)

# def _concentration_limit(self, symbol: str, price: float) -> int:
#     """集中度限制"""
#     current_value = self.pm.get_position(symbol).market_value
#     max_additional = (
#         self.params.max_position_ratio * self.pm.total_equity - current_value
#     )
#     return int(max_additional // price)

# def _leverage_constraint(self, required_cash: float) -> int:
#     """杠杆限制"""
#     available_with_leverage = (
#         self.pm.available_cash * self.params.max_leverage
#     )
#     return int(available_with_leverage // required_cash)

# def _round_lot(self, size: int) -> int:
#     """整手数处理（A股标准）"""
#     return (size // 100) * 100

# def generate_stop_levels(
#     self,
#     symbol: str,
#     entry_price: float,
#     direction: OrderDirection
# ) -> Dict[str, float]:
#     """生成动态止损止盈价位"""
#     atr = self.volatility_calc(symbol, self.params.volatility_window)
#     if direction == OrderDirection.BUY:
#         stop_loss = entry_price * (1 - self.params.stop_loss_pct)
#         take_profit = entry_price * (1 + self.params.take_profit_pct)
#         # 波动率调整
#         trailing_stop = entry_price - 2 * atr
#     else:
#         stop_loss = entry_price * (1 + self.params.stop_loss_pct)
#         take_profit = entry_price * (1 - self.params.take_profit_pct)
#         trailing_stop = entry_price + 2 * atr

#     return {
#         'stop_loss': stop_loss,
#         'take_profit': take_profit,
#         'trailing_stop': trailing_stop
#     }

# def check_portfolio_risk(self) -> bool:
#     """整体组合风险检查"""
#     total_risk = sum(
#         p.market_value / self.pm.total_equity
#         for p in self.pm.positions.values()
#     )

#     return total_risk <= self.params.max_portfolio_risk